Submitted:
20 December 2024
Posted:
23 December 2024
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Abstract
Background: Endometrial cancer (EC) incidence and mortality have been steadily rising globally over recent decades. The introduction of advanced molecular technologies, such as next-generation sequencing (NGS), alongside the FIGO 2023 classification, presents opportunities for refined diagnostics and risk stratification. This study aimed to analyze differences in EC classification among oncology centers in southeastern Poland.
Methods: Data were collected from 461 consecutive patients newly diagnosed with EC between 2022 and 2024 at four major oncology centers in southeastern Poland. Molecular and immunohistochemical (IHC) analyses were conducted on formalin-fixed paraffin-embedded (FFPE) tissues to identify key markers, including POLE mutations, MSI-H, and p53 status.
Results: The application of the FIGO 2023 staging system revealed statistically significant inter-center differences, with Centers 1 and 4 diagnosing a higher proportion of early-stage cases. The most prevalent subtype was NSMP, observed in 51% of cases. MSI-H occurred in 13%-36% of patients, depending on the center. p53 mutations ranged from 9% to 26%. POLE mutations were identified in 4% overall. Significant variations in molecular subtype distribution across centers highlight potential differences in diagnostic access or tumor biology. Conclusions: The findings demonstrate regional differences in EC staging and molecular profiles in Poland, potentially reflecting disparities in diagnostic resources, methodologies, or tumor characteristics. Addressing these variations through standardized diagnostic protocols and equitable access to molecular tools is critical for optimizing patient outcomes. Future research should focus on evaluating the impact of molecular markers on therapy response and prognosis to guide personalized treatment strategies.
Keywords:
cancer
; DNA polymerase epsilon
; MSI
; p53
; molecular classification
; FIGO 2023
1. Introduction
Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with both incidence and mortality rates rising in recent years. This trend highlights the critical need for advancements in diagnostic and therapeutic strategies. The updated 2023 FIGO classification represents a significant milestone by incorporating molecular markers into traditional anatomical staging. These markers, including DNA polymerase epsilon (POLE) mutations, p53 status, and microsatellite instability (MSI-H), are now recognized as key predictive and prognostic factors in EC [1].
Modern EC diagnostics leverage a combination of next-generation sequencing (NGS), Sanger sequencing (PCR), and traditional immunohistochemistry (IHC). The gold standard integrates molecular diagnostics for POLE mutations, mismatch repair (MMR) proteins, and p53 into a comprehensive approach such as the PROMISE algorithm [2]. While some oncology centers exclusively use molecular techniques like NGS and PCR, this approach is supported by international guidelines [3]. These technological advancements are pivotal for achieving more precise diagnostic insights and facilitating personalized treatment.
This study represents the first comprehensive analysis of the prevalence of key molecular features of EC in Poland. It evaluates the implementation of the FIGO 2023 classification in oncology centers across southeastern Poland. Specifically, the study aims to:
- Identify differences in staging and molecular subtype classification among centers.
- Highlight regional disparities in the use of advanced molecular diagnostics.
The findings contribute to the growing body of evidence regarding FIGO 2023's clinical utility and underscore the importance of diagnostic standardization for optimizing treatment outcomes. By addressing gaps in molecular and clinical practices, this research offers valuable insights for improving patient care both regionally and globally.
2. Materials and Methods
2.1. Study Design and Population
This study included consecutive patients newly diagnosed with endometrial cancer (EC) between April 2022 and April 2024. The patients were treated at four major gynecologic oncology centers in southeastern Poland, located in the Silesian, Lesser Poland, Subcarpathian, and Lublin Voivodeships. Cases without complete medical records or treated prior to the implementation of the FIGO 2023 classification were excluded. Molecular and immunohistochemical (IHC) analyses were performed on surgical specimens obtained during hysterectomy procedures.
2.2. Immunohistochemistry (IHC) Analysis
IHC analyses of MLH, MSH, PMS, and p53 proteins were performed using OptiView and UltraView kits (Ventana) on the BenchMark Ultra system.
2.3. DNA Extraction
DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue samples. Pathologists pre-assessed the tissue blocks to select the most suitable samples for molecular analysis and to evaluate the percentage of tumor cells. The following kits were used for DNA isolation:
QIAamp DSP DNA FFPE Tissue Kit (Qiagen)
Maxwell® RSC DNA FFPE Kit and Maxwell® RSC Instrument (Promega)
2.4. Molecular Analysis
POLE Sequencing: Sanger sequencing was conducted on exons 9, 11, 13, and 14 of the POLEgene.
NGS Analysis: Next-generation sequencing (NGS) was performed on the IonTorrent platform using a custom-designed panel (Thermo Fisher Scientific Ion AmpliSeq Designer). The panel targeted key genes, including MLH1, MSH2, MSH6, PMS2, POLE, and TP53. Sequencing was carried out on CHEF and S5 instruments with Ion 510™, Ion 520™, and Ion 530™ kits (Thermo Fisher Scientific).
2.5. Variant Classification
Detected genetic variants were categorized into five classes:
Pathogenic, Likely pathogenic, Variants of unknown significance (VUS), Likely benign, Benign
Bioinformatics tools and databases, including Cancer Genome Interpreter, Varsome, ClinVar, OncoKB, and Franklin, were utilized for variant classification. Polymorphisms, benign, likely benign, and VUS variants were excluded from the final analysis.
2.6. Ethical Considerations
All data were anonymized before analysis to ensure compliance with data protection regulations.
3. Results
Clinical, microscopic, and molecular data were collected for 461 patients diagnosed with endometrial cancer (EC) across four oncology centers in southeastern Poland. The mean age of the patients was 65.8 years, with no statistically significant differences observed in mean age between the centers. The histological subtypes of EC were distributed as presented in Table 1, showing significant inter-center variability.
Molecular analyses revealed that the most common molecular subtype was NSMP, representing 51% of cases. Microsatellite instability (MSI-H) was identified in 13%–36% of patients depending on the center, while p53 mutations ranged from 9% to 26%. POLE mutations were observed in 4% of all cases. Differences in molecular subtype distributions were statistically significant across the centers, indicating variability in the prevalence of key molecular features.
Additionally, staging according to the FIGO 2023 classification showed significant inter-center differences. Centers 1 and 4 had a higher proportion of early-stage cases, while Centers 2 and 3 reported more advanced-stage cases.
Table 1.
Analysis of histological types in individual centers.
| Center 1 |
Center2 | Center 3 | Center 4 | Total | statistical significance p |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | % | N | % | n | % | N | % | n | % | |||
| Non-aggressive types | p<0,001 | |||||||||||
| Endometrioid carcinoma G1/G2 | 69 | 74,2 | 79 | 62,7 | 53 | 76,8 | 156 | 90,2 | 357 | 77,4 | ||
| Aggressive types | ||||||||||||
| Endometrioid carcinoma G3 | 11 | 11,8 | 35 | 27,9 | 9 | 13,0 | 7 | 4,0 | 62 | 13,4 | ||
| Serous carcinoma | 7 | 7,6 | 7 | 5,5 | 4 | 5,9 | 3 | 1,8 | 21 | 4,5 | ||
| other | 6 | 6,4 | 5 | 3,9 | 3 | 4,3 | 7 | 4,0 | 22 | 4,7 | ||
Table 2.
Analysis of Myometrial and Cervical Stroma Invasion by Individual Centers.
| Center 1 |
Center 2 |
Center 3 |
Center 4 |
Total | statistical significance p |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | n | % | ||
| Myometrial invasion | p=0,151 | ||||||||||
| limited to the endometrium | 4 | 4,3 | 3 | 2,3 | 6 | 8,7 | 6 | 3,5 | 19 | 4,1 | |
| invasion of less than half | 46 | 49,5 | 60 | 47,6 | 33 | 47,8 | 92 | 53,2 | 231 | 50,0 | |
| invasion of half or more | 40 | 43,0 | 63 | 50,0 | 27 | 39,1 | 67 | 38,7 | 197 | 42,7 | |
| Invasion of uterine serosa | 3 | 3,2 | 0 | 0 | 3 | 4,3 | 8 | 4,6 | 14 | 3,0 | |
| Invasion of cervical stroma | 14 | 15,1 | 24 | 19,1 | 7 | 10,1 | 33 | 19,1 | 68 | 14,7 | p=0,326 |
Table 3.
Analysis of LVSI and Lymph Node Involvement by Individual Centers.
| Center 1 |
Center 2 |
Center 3 |
Center 4 |
Total | statistical significance p |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| n | % | N | % | n | % | N | % | n | % | ||
| LVSI |
p=0,008 |
||||||||||
| substantial LVSI | 28 | 30,1 | 34 | 26,9 | 16 | 23,2 | 61 | 35,3 | 139 | 30,1 | |
| focal LVSI | 10 | 10,7 | 13 | 10,3 | 4 | 5,8 | 2 | 1,2 | 29 | 6,3 | |
| Metastasis to the pelvic lymph nodes | p=0,413 |
||||||||||
| makroprzerzuty | 8 | 8,6 | 7 | 5,6 | 4 | 5,8 | 14 | 8,1 | 33 | 7,2 | |
| mikroprzerzuty | 2 | 2,2 | 1 | 0,8 | 0 | 0 | 0 | 0 | 2 | 0,4 | |
| Metastasis to para-aortic lymph nodes |
p=0,016 |
||||||||||
| Macrometastasis | 5 | 5,4 | 2 | 1,6 | 1 | 1,5 | 0 | 0 | 8 | 1,7 | |
| Micrometastasis | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Table 4.
Distribution of FIGO 2023 Staging Across Individual Centers.
| Center 1 |
Center 2 |
Center 3 |
Center 4 |
Total | statistical significance p |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| N | % | n | % | n | % | n | % | n | % | ||
| I | 57 | 61 | 68 | 55 | 33 | 48 | 81 | 47 | 239 | 52 |
p=0,019 |
| IA | 40 | 44 | 46 | 35 | 19 | 27 | 68 | 40 | |||
| IB | 17 | 18 | 21 | 17 | 12 | 17 | 12 | 6 | |||
| IC | 0 | 0 | 1 | 1 | 2 | 3 | 1 | 0,5 | |||
| II | 13 | 14 | 39 | 30 | 28 | 40 | 62 | 36 | 142 | 31 | |
| IIA | 4 | 4 | 4 | 3 | 3 | 4 | 13 | 7 | |||
| IIB | 1 | 1 | 12 | 10 | 7 | 10 | 26 | 15 | |||
| IIC | 8 | 9 | 23 | 20 | 18 | 26 | 23 | 13 | |||
| III | 21 | 22 | 17 | 13 | 7 | 10 | 28 | 16 | 73 | 16 | |
| IIIA | 5 | 6 | 3 | 2 | 2 | 3 | 4 | 2 | |||
| IIIB | 1 | 1 | 4 | 3 | 2 | 3 | 9 | 5 | |||
| IIIC | 15 | 16 | 10 | 8 | 3 | 4 | 15 | 8 | |||
| IV | 2 | 3 | 2 | 2 | 1 | 2 | 2 | 1 | 7 | 1 | |
| IVA | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |||
| IVB | 0 | 0 | 2 | 2 | 1 | 1 | 2 | 1 | |||
| Total | 93 | 100 | 126 | 100 | 69 | 100 | 173 | 100 | 461 | 100 | |
Table 5.
Analysis of Molecular Features by Individual Centers.
| Center 1 |
Center 2 |
Center 3 |
Center 4 |
Total | p | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| NGS/Sanger/IHC | n | % | N | % | n | % | n | % | n | % | |
| POLE | 7 | 7 | 4 | 3 | 3 | 4 | 7 | 4 | 21 | 4 |
p=0,018 |
| MSI-H | 23 | 24 | 45 | 36 | 9 | 13 | 49 | 28 | 126 | 27 | |
| p53 | 18 | 19 | 11 | 9 | 17 | 26 | 31 | 18 | 77 | 18 | |
| NSMP | 45 | 50 | 66 | 52 | 40 | 57 | 86 | 50 | 227 | 51 | |
| 93 | 100 | 126 | 100 | 69 | 100 | 173 | 100 | 461 | 100 | ||
4. Discussion
The 2023 FIGO classification for endometrial cancer (EC) represents a significant advance in personalized medicine by integrating traditional anatomical criteria with critical pathological parameters, such as histological subtype, histopathological grade, the presence of lymphovascular space invasion (LVSI), and molecular alterations including POLE mutations, p53 status, and MSI-H [2]. This approach enhances prognostic precision by differentiating aggressive subtypes—serous, clear cell, poorly differentiated endometrioid, mucinous, mesonephric, gastrointestinal type, undifferentiated carcinomas, and carcinosarcomas—from less aggressive subtypes such as G1/G2 endometrioid carcinoma. Moreover, incorporating aggressive features like LVSI in staging has shifted treatment paradigms, particularly in tailoring adjuvant therapies to improve patient outcomes [4,5].
Our study revealed significant inter-center variability in the application of the FIGO 2023 classification, highlighting regional disparities in Poland. Centers 1 and 4 had a higher proportion of early-stage diagnoses, which could reflect better access to advanced diagnostic tools and greater patient awareness of early symptoms. In contrast, Centers 2 and 3 reported a higher percentage of advanced cases, potentially due to limited access to specialized care or delays in diagnosis. These findings emphasize how infrastructure and healthcare access can influence the clinical stage at diagnosis and subsequent management.
4.1. Molecular Profiles
Significant differences in molecular subtype distributions were also observed. For instance, p53 mutations were detected in 27% of cases in Center 3 compared to only 9% in Center 2. Variability in the detection of molecular markers such as MSI-H (13%-36%) and POLE mutations (4%) highlights the lack of standardized diagnostic protocols across centers. This variability likely stems from the use of different diagnostic tools—ranging from next-generation sequencing (NGS) to immunohistochemistry (IHC)—and local differences in testing practices, which aligns with findings in other studies [8,9,12].
4.2. Comparison with International Data:
When comparing these results with international benchmarks, similarities and discrepancies are evident. For example, POLE mutations in our study (4%) are slightly lower than the 7% reported in TCGA [10] but align with findings in ProMisE studies, where POLE mutations are observed in 5–12% of cases [11]. Similarly, the MSI-H subtype (13%-36%) reflects variability consistent with TCGA findings, which report a prevalence of 28% [10].
For p53 mutations, our study shows rates of 9%-26%, aligning with TCGA data, where p53 abnormalities are predominantly found in the copy-number high (CNH) subtype, which comprises 26% of all endometrial carcinoma cases and is strongly associated with serous carcinoma and poor prognosis [10]. Similarly, the NSMP subtype, representing 51% of cases in our cohort, is consistent with findings from ProMisE studies, where NSMP accounts for approximately 40%-50% of cases [18]. This molecular subtype typically exhibits low levels of genomic instability and an intermediate prognosis. These comparisons underscore the congruence of molecular patterns between Polish and international data while highlighting the necessity of standardizing molecular diagnostic practices to reduce inter-center variability and ensure robust classification.
4.3. Challenges in Pathological Evaluation:
Our findings echo previous studies that identified significant challenges in histopathological evaluation. Retrospective analyses, such as PORTEC-3, demonstrated reclassification rates as high as 43% after central review, while Grevenkamp et al. reported critical discrepancies in 9.7% of cases, which directly influenced therapeutic decisions [14,15]. These observations underscore the need for centralized reviews and stricter adherence to standardized guidelines.
4.4. Standardization Issues in LVSI Assessment:
Defining significant LVSI remains inconsistent across international guidelines. While FIGO 2023, WHO 2020, and ESGO/ESTRO/ESP guidelines define LVSI involvement as five or more lymphovascular spaces, the NCCN recommends a threshold of four spaces on a single H&E slide. This lack of uniformity introduces the risk of “stage drift,” complicating comparisons of treatment outcomes and prognostic evaluations between institutions [16].
4.5. Future Directions:
Our study highlights the urgent need for the standardization of diagnostic protocols and equitable access to advanced molecular tools across all centers. Centralized pathology reviews and the adoption of uniform criteria for molecular diagnostics, such as the PROMISE algorithm, could significantly improve consistency in EC classification and management. Future research should focus on evaluating how molecular markers such as p53, MSI-H, and POLE mutations influence treatment responses and outcomes. This could guide the development of more tailored therapeutic strategies and improve outcomes for EC patients globally.
4.6. Strengths and Limitations:
This study is the first in the literature to examine EC molecular profiles within the Polish population. The geographically coherent data and the inclusion of consecutive cases strengthen its reliability. However, variability in genetic testing methods and the combination of molecular and immunohistochemical approaches across centers may have influenced the results. While this reflects real-world clinical practice, it underscores the need for greater methodological standardization in future studies.
5. Conclusions
Our study highlights significant variability in the application of the FIGO 2023 classification for endometrial cancer, particularly in staging and molecular profiling, across different oncology centers in southeastern Poland. These differences underscore the urgent need for diagnostic standardization and equitable access to advanced molecular tools. By adopting uniform protocols and ensuring consistency in diagnostic approaches, the clinical utility of the FIGO 2023 classification can be fully realized. Future research should focus on evaluating the influence of molecular markers on treatment response and prognosis, thereby supporting the development of more personalized therapeutic strategies for endometrial cancer patients both in Poland and globally.
Author Contributions
For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used “Conceptualization, W.Sz. M.N-J., P.B. ; methodology, W.Sz, T.K., P.B.; software,W.Sz, M.N.-J.; validation, W.Sz. P.B. formal analysis W.Sz. M.N.-J. P.B.; investigation W.Sz.,T.K., M.Ś. M.C.-S, M.N-J., I.W. J.T., P.B.; resources W.Sz, M.C-S. M.Ś, I.W. J.T.; data curation W.Sz.,T.K., M.Ś. M.C.-S, M.N-J., I.W. J.T., P.B, X.X.; writing—original draft preparation W.Sz. M.N-J, P.B.; writing—review and editing W.Sz. M.N-J, P.B.;.; visualization, W.Sz. M.N-J, P.B.; X.X.; supervision,P.B.; project administration, W.Sz, M.N-J..; All authors have read and agreed to the published version of the manuscript.
Funding
“This research received no external funding”.
Institutional Review Board Statement
The study did not require ethical approval.
Informed Consent Statement
“Not applicable.”.\
Informed Consent Statement
Any research article describing a study involving humans should contain this statement. Please add “Informed consent was obtained from all subjects involved in the study.” OR “Patient consent was waived due to REASON (please provide a detailed justification).” OR “Not applicable.” for studies not involving humans. You might also choose to exclude this statement if the study did not involve humans.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).
Conflicts of Interest
“The authors declare no conflicts of interest.
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